Digital Twin-Driven Lifelong Learning Systems

As technological change reshapes learning, digital twins in education systems transform education and skill development. A digital twin, a virtual representation of a real-world entity, can model individuals' knowledge, competencies, and learning behaviors over time. By integrating data from educational platforms, workplaces, and personal goals, these systems enable personalized learning paths that adapt to an individual's progress and needs. They offer targeted recommendations, real-time feedback, and predictive insights that support continuous growth. This convergence of advanced analytics and human-centered design could make lifelong learning more responsive, efficient, and aligned with the demands of a digital economy. Digital Twin-Driven Lifelong Learning Systems introduces and develops a new paradigm in education in which the digital twin acts as the core of designing and managing lifelong learning paths. It bridges education, skills training, and the real needs of the labor market, showing how a personalized and intelligent learning ecosystem can be designed and implemented at an individual and organizational scale. This book covers topics such as education systems, personalized learning, and data governance, and is a useful resource for educators, engineers, academicians, researchers, and scientists.